Databases are typically relied upon to store large amounts of data. One exemplary type of database system includes the On-Line Analytical Processing (OLAP) database system. A multi-dimensional OLAP database system has multiple dimensions and members within the dimensions. The data for these dimensions and members may be stored in a table. In use, when these dimensions are changed, data in the table is modified.
Over time as the OLAP database system is relied upon to continuously store more and more data, the resources of the OLAP database system eventually become strained (e.g. data volume threatens to exceed system resources, dimension table size becomes unmanageable, etc.). Moreover, any attempt to remove older data requires significant effort (e.g. data reloading, etc.).
There is thus a need for more effectively managing aging data and/or other related issues associated with the prior art.